A5037523915- Non-Invasive Vital Sign Monitoring
- Hemodynamic Monitoring and Therapy
- Heart Rate Variability and Autonomic Control
- Context-Aware Activity Recognition Systems
- Blood Pressure and Hypertension Studies
- Gait Recognition and Analysis
- ECG Monitoring and Analysis
- Human Mobility and Location-Based Analysis
- COVID-19 epidemiological studies
- Healthcare Technology and Patient Monitoring
- Anomaly Detection Techniques and Applications
- Mobile Health and mHealth Applications
- EEG and Brain-Computer Interfaces
- Optical Imaging and Spectroscopy Techniques
- COVID-19 Pandemic Impacts
- Tactile and Sensory Interactions
- Emotion and Mood Recognition
- Privacy-Preserving Technologies in Data
- Heart Failure Treatment and Management
- Autism Spectrum Disorder Research
- Data Stream Mining Techniques
- Neural Networks and Applications
- Down syndrome and intellectual disability research
- Smart Grid Energy Management
- Energy Efficient Wireless Sensor Networks
Jožef Stefan Institute
2016-2024
Jožef Stefan International Postgraduate School
2020-2024
Blood pressure (BP) is a direct indicator of hypertension, dangerous and potentially deadly condition. Regular monitoring BP thus important, but many people have aversion towards cuff-based devices, their limitation that they can only be used at rest. Using just photoplethysmogram (PPG) to estimate potential solution investigated in our study. We analyzed the MIMIC III database for high-quality PPG arterial waveforms, resulting over 700 h signals after preprocessing, belonging 510 subjects....
Human Sensing, a field that leverages technology to monitor human activities, psycho-physiological states, and interactions with the environment, enhances our understanding of behavior drives development advanced services improve overall quality life. However, its reliance on detailed often privacy-sensitive data as basis for machine learning (ML) models raises significant legal ethical concerns. The recently proposed ML approach Federated Learning (FL) promises alleviate many these...
We present a study of buzzing sounds several common species bumblebees, with the focus on automatic classification bumblebee and types. Such is useful for monitoring, which important in view evaluating quality their living environment protecting biodiversity these pollinators. analysed natural frequencies queens workers 12 species. In addition, we changes Bombus hypnorum worker different types behaviour. developed application using machine learning algorithms. extracted audio features from...
Background Congestive heart failure (CHF) is a disease that requires complex management involving multiple medications, exercise, and lifestyle changes. It mainly affects older patients with depression anxiety, who commonly find difficult. Existing mobile apps supporting the self-management of CHF have limited features are inadequately validated. Objective The HeartMan project aims to develop personal health system would comprehensively address by using sensing devices artificial...
The Sussex-Huawei Locomotion-Transportation recognition challenge presents a unique opportunity to the activity-recognition community - providing large, real-life dataset with activities different from those typically being recognized. This paper describes our submission (team JSI Classic) competition that was organized by authors. We used carefully executed machine learning approach, achieving 90% accuracy classifying eight (Still, Walk, Run, Bike, Car, Bus, Train, Subway). first step data...
In recent years, activity recognition (AR) has become prominent in ubiquitous systems. Following this trend, the Sussex-Huawei Locomotion-Transportation (SHL) challenge provides a unique opportunity for researchers to test their AR methods against common, real-life and large-scale benchmark. The goal of is recognize eight everyday activities including transit. Our team, JSI-Deep, utilized an approach based on combining multiple machine-learning following principle knowledge. We first created...
Contact-free sensing gained much traction in the past decade. While remote monitoring of some parameters (heart rate) is approaching clinical levels precision, others remain challenging (blood pressure). We investigated feasibility estimating blood pressure (BP) via pulse transit time (PTT) a novel single-site manner, using modified RGB camera. A narrow-band triple band-pass filter allowed us to measure PTT between different skin layers, harvesting information from green and near-infrared...
Electrocardiogram (ECG) reconstruction from contact photoplethysmogram (PPG) would be transformative for cardiac monitoring. We investigated the fundamental and practical feasibility of such by first replicating pioneering work in field, with aim assessing methods evaluation metrics used. then expanded existing research investigating different cycle segmentation scenarios to robustly verify both feasibility, as well potential. found that using discrete cosine transform (DCT) a linear ridge...
This paper presents a contact-free method for physiological parameter estimation in people with profound intellectual and multiple disabilities (PIMD). We used an existing state-of-the-art algorithm Plane-Orthogonal-to-Skin (POS) order to obtain initial remote photoplethysmogram (rPPG) reconstruction from facial videos. enhanced this signal by applying long-short-term-memory (LSTM) neural network the PPG reconstruction. Evaluation of our on public database DEAP has shown heart rate (HR)...
Contact-free sensors offer important advantages compared to traditional wearables. Radio-frequency (e.g., radars) the means monitor cardiorespiratory activity of people without compromising their privacy, however, only limited information can be obtained via movement, traditionally related heart or breathing rate. We investigated whether five complex hemodynamics scenarios (resting, apnea simulation, Valsalva maneuver, tilt up and down on a table) classified directly from publicly available...
The COVID-19 pandemic affected the whole world, but not all countries were impacted equally. This opens question of what factors can explain initial faster spread in some compared to others. Many such are overshadowed by effect countermeasures, so we studied early phases infection when countermeasures had yet taken place. We collected most diverse dataset potentially relevant and metrics date for this task. Using it, show importance different factor categories as determined both statistical...
UPDATED---August 17, 2018. Blood pressure (BP) is the most commonly performed medical office test. We developed a system that uses exclusively wristband-collected photoplethysmogram (PPG) to estimate BP. A dataset was collected and annotated during daily activities of 22 subjects. Preprocessing applied remove signal noise artefacts. Signal segmented into cycles features were computed. The RReliefF algorithm used select subset relevant features. approach validated with person-independent...
The preferences of people with profound intellectual and multiple disabilities (PIMD) often remain unfulfilled since it stays challenging to decode their idiosyncratic behavior resulting in a negative impact on quality life (QoL). Physiological data (i.e. heart rate (variability) motion data) might be the missing piece for identifying emotions PIMD, which positively affects QoL.
Single-site multi-wavelength (MW) pulse transit time (PTT) measurement was recently proposed using contact sensors with sequential illumination. It leverages different penetration depths of light to measure the traversal a cardiac between skin layers. This enabled continuous single-site MW blood pressure (BP) monitoring, but faces challenges like subtle compression, which importantly influences PPG morphology and subsequent PTT. We extended this idea contact-free camera-based sensing...
Contact-free remote sensing gained much traction in the past decade. While such monitoring of some vitals (heart rate) is approaching clinical levels performance, others remain difficult to estimate (blood pressure) while being very valuable. In this paper we investigated feasibility estimating pulse transit time (PTT) - a marker known be highly correlated with blood pressure way from single measuring site, using just modified RGB camera. The replacement infrared (IR) filter narrow band...
<sec> <title>BACKGROUND</title> Congestive heart failure (CHF) is a disease that requires complex management involving multiple medications, exercise, and lifestyle changes. It mainly affects older patients with depression anxiety, who commonly find difficult. Existing mobile apps supporting the self-management of CHF have limited features are inadequately validated. </sec> <title>OBJECTIVE</title> The HeartMan project aims to develop personal health system would comprehensively address by...
Contact-free remote sensing is showing increasing potential for real-life use, especially screening applications (e.g., thermal cameras to detect fever). We investigated the feasibility of estimating pulse transit time (PTT) – a marker known be highly correlated with blood pressure in way from single measuring site, using just modified RGB camera. replaced default infrared (IR) filter narrow-band triple-bandpass allowing us remotely measure PTT between green and near-infrared (NIR)...